Reviews
3 February 2015

Diagnostic and Predictive Accuracy of Blood Pressure Screening Methods With Consideration of Rescreening Intervals: A Systematic Review for the U.S. Preventive Services Task ForceFREE

Publication: Annals of Internal Medicine
Volume 162, Number 3

Abstract

Background:

Elevated blood pressure (BP) is the largest contributing risk factor to all-cause and cardiovascular mortality.

Purpose:

To update a systematic review on the benefits and harms of screening for high BP in adults and to summarize evidence on rescreening intervals and diagnostic and predictive accuracy of different BP methods for cardiovascular events.

Data Sources:

Selected databases searched through 24 February 2014.

Study Selection:

Fair- and good-quality trials and diagnostic accuracy and cohort studies conducted in adults and published in English.

Data Extraction:

One investigator abstracted data, and a second checked for accuracy. Study quality was dual-reviewed.

Data Synthesis:

Ambulatory BP monitoring (ABPM) predicted long-term cardiovascular outcomes independently of office BP (hazard ratio range, 1.28 to 1.40, in 11 studies). Across 27 studies, 35% to 95% of persons with an elevated BP at screening remained hypertensive after nonoffice confirmatory testing. Cardiovascular outcomes in persons who were normotensive after confirmatory testing (isolated clinic hypertension) were similar to outcomes in those who were normotensive at screening. In 40 studies, hypertension incidence after rescreening varied considerably at each yearly interval up to 6 years. Intrastudy comparisons showed at least 2-fold higher incidence in older adults, those with high-normal BP, overweight and obese persons, and African Americans.

Limitation:

Few diagnostic accuracy studies of office BP methods and protocols in untreated adults.

Conclusion:

Evidence supports ABPM as the reference standard for confirming elevated office BP screening results to avoid misdiagnosis and overtreatment of persons with isolated clinic hypertension. Persons with BP in the high-normal range, older persons, those with an above-normal body mass index, and African Americans are at higher risk for hypertension on rescreening within 6 years than are persons without these risk factors.

Primary Funding Source:

Agency for Healthcare Research and Quality.
Nearly 1 in 3 U.S. adults has high blood pressure (BP), including two thirds of those aged 60 years or older (1). Elevated BP is the largest contributing risk factor to all-cause and cardiovascular mortality (2). Despite the clear importance of accurate diagnosis of high BP, recommendations for BP measurement protocols and rescreening intervals are not based on systematic reviews of the literature (3, 4), and recommended protocols, such as repeated measurements, are rarely followed in routine health care settings (5–9). To help address these issues, newer measurement methods have been developed to reduce error, simplify performance of repeated measurements, evaluate BP throughout the 24-hour cycle, and allow use in nonmedical settings. Evidence-based measurement methods and rescreening intervals could improve the benefits and efficiency of BP screening.
In 2007, the U.S. Preventive Services Task Force (USPSTF) reaffirmed its 2003 A recommendation to screen for high BP in adults aged 18 years or older (10). In 2003, a synthesis of indirect evidence for BP screening found good-quality evidence that treatment of high BP in adults substantially decreases the incidence of cardiovascular events (11). Both reviews found that screening and treatment for high BP cause few major harms (11, 12). Given the strong evidence base for the previous recommendations and recently updated guidelines for BP control (4, 13), the USPSTF did not believe that updating the indirect evidence path was necessary. However, the previous systematic reviews did not identify a BP measurement reference standard, address diagnostic accuracy of BP measurement methods and protocols, or determine the most appropriate rescreening interval. Our evidence review was designed to address these important aspects of screening for high BP and update the direct evidence of benefits and harms of screening.

Methods

To conduct this review, we developed an analytic framework with 5 key questions (Appendix Figure 1) that examined direct evidence for the benefits and harms of screening for high BP (key questions 1 and 5, respectively), diagnostic accuracy of office BP measurement (OBPM) (key question 2), prediction of cardiovascular events by BP method and diagnostic accuracy of nonoffice measurement (key question 3), and rescreening interval (key question 4). Detailed methods are available in our full evidence report (14). The analytic framework, review questions, and methods for locating and qualifying evidence were posted on the USPSTF Web site for public comment before we started the review, and the final versions reflect public input.
Appendix Figure 1. Analytic framework. ABPM = ambulatory blood pressure monitoring; BP = blood pressure; CHD = coronary heart disease; CVD = cardiovascular disease; ESKD = end-stage kidney disease; HBPM = home blood pressure monitoring; HF = heart failure. * Defined as the threshold for pharmacologic treatment.
Appendix Figure 1. Analytic framework.
ABPM = ambulatory blood pressure monitoring; BP = blood pressure; CHD = coronary heart disease; CVD = cardiovascular disease; ESKD = end-stage kidney disease; HBPM = home blood pressure monitoring; HF = heart failure.
* Defined as the threshold for pharmacologic treatment.

Data Sources and Searches

We searched MEDLINE, PubMed, the Cochrane Central Register of Controlled Trials, and CINAHL from 2003 through 8 August 2014 to update benefits and harms of screening for high BP. We searched the same databases (excluding CINAHL) through 24 February 2014 as follows: starting in 1992 (to allow for implementation of the first guidelines for validation of BP monitoring devices [15]) for prediction of cardiovascular events by BP method and diagnostic accuracy of nonoffice measurement, and starting in 1966 (the beginning of MEDLINE) for rescreening interval. On the basis of the findings from these updated searches, we did not further update them because any studies we found would probably not have changed the overall conclusions. We also searched bibliographies of relevant reviews, included studies, and publication lists of highly referenced studies.

Study Selection

Two investigators independently reviewed abstracts and full-text articles against prespecified inclusion and exclusion criteria (14). We required all studies to have enrolled untreated adults and to have been conducted in countries rated as “very high” on the 2013 Human Development Index (16). For prediction of cardiovascular events, we allowed studies that included treated patients because a proportion of persons followed over time would inevitably begin treatment. Ambulatory BP monitoring (ABPM) and home BP monitoring (HBPM) devices were eligible for use in confirming an initially elevated OBPM result. For screening benefits and harms, cardiovascular events we analyzed included fatal or nonfatal myocardial infarction; sudden cardiac death; stroke; heart failure; atrial fibrillation; transient ischemic attack; end-stage kidney disease; or a composite of any of the aforementioned events, excluding cardiovascular symptoms, angina, revascularization, carotid intima–media thickness, and left ventricular hypertrophy.
For diagnostic accuracy of OBPM, we included studies that compared different office-based devices or measurement protocols and reported sensitivity, specificity, predictive values, or concordance (for example, κ). For diagnostic accuracy of confirmatory BP measurement methods, eligible study populations had an initial elevated office BP at screening, which allowed for reporting or calculation of the positive predictive value (PPV).
For prediction of cardiovascular events, eligible studies followed a cohort of patients over time and reported the associations (hazard or risk ratios) of BP as a continuous variable, measured by at least 2 methods at baseline, with data on overall mortality or cardiovascular events collected during follow-up. For rescreening interval, we included studies that followed cohorts of initially nonhypertensive adults over time and reported hypertension incidence at rescreening intervals of up to 6 years.

Data Extraction and Quality Assessment

One investigator abstracted data from all included studies, and a second checked for accuracy. Two investigators independently assessed the quality of included studies by using predefined, design-specific criteria (17–19). We rated study quality as good, fair, or poor and excluded all poor-quality studies (17). We resolved disagreements about quality through discussion with a third investigator. Where reported, studies with various threats to internal validity were downgraded to fair-quality according to USPSTF standards (17).

Data Synthesis and Analysis

We qualitatively described the results on the benefits and harms of screening. Per our protocol, we first calculated the diagnostic accuracy of OBPM by using the recommendations of the American Heart Association as the reference standard because there is no gold standard for BP measurement (3). With the subsequent identification of ABPM as the best predictor of cardiovascular events, we calculated the diagnostic accuracy of OBPM and confirmatory BP measurement methods by using ABPM as the reference standard where possible. We qualitatively described all diagnostic accuracy results because data were insufficient for quantitative synthesis.
For prediction of cardiovascular events, we combined fatal and nonfatal events within outcome categories (cardiovascular, stroke, and cardiac). Risk was most commonly reported as the hazard ratio associated with each 10–mm Hg increase in systolic BP and each 5–mm Hg increase in diastolic BP. We converted hazard ratios to these common increments if they were reported differently (14). We depicted the hazard ratios in forest plots for qualitative evaluation; because of the small numbers of studies for each outcome and heterogeneity across studies, we did not calculate summary meta-analytic estimates of risk to determine the best BP measurement method for prediction. We conducted exploratory meta-analyses to compare ABPM protocols (24-hour, daytime, and nighttime) by generating estimates of cardiovascular events or mortality risk for each protocol by using the DerSimonian–Laird random-effects method (20). In sensitivity analyses, these results were compared to estimates generated by using profile likelihood (21) and Knapp–Hartung methods (22).
For rescreening, we pooled reported incidence rates across all studies to generate a weighted mean incidence at yearly intervals (reported within ± 0.5 year). We qualitatively examined within-study comparisons among a priori subgroups of age, BP, sex, body mass index (BMI), smoking status, and race/ethnicity (14).
When constructing the overall summary of evidence (Appendix Table 1), we evaluated included studies within the context of each review question for consistency of results for important outcomes and relevance to primary care.
Appendix Table 1. Overall Summary of Evidence, by Key Question
Appendix Table 1. Overall Summary of Evidence, by Key Question

Role of the Funding Source

Staff from the Agency for Healthcare Research and Quality (AHRQ) provided oversight for the project and assisted in external review of the companion draft evidence synthesis. Liaisons for the USPSTF helped to resolve issues about the scope of the review but were not involved in the conduct of the review.

Results

We reviewed 19 309 abstracts and 1171 articles for possible inclusion (Appendix Figure 2).
Appendix Figure 2. Summary of evidence search and selection. KQ = key question. * Surveillance search results through August 2014 for trials reporting direct benefits of screening were not included; no additional trials were identified.
Appendix Figure 2. Summary of evidence search and selection.
KQ = key question.
* Surveillance search results through August 2014 for trials reporting direct benefits of screening were not included; no additional trials were identified.

Benefits of Screening for High BP

For direct evidence of screening benefit, we included only randomized, controlled trials (RCTs) that reported changes in health outcomes as a result of screening for hypertension compared with no screening. We identified 1 good-quality cluster RCT of a community pharmacy–based BP screening program targeting adults aged 65 years or older (23). Trained volunteer health educators also provided participants with educational materials and resources to support self-management. This trial found fewer annual composite cardiovascular-related hospitalizations in the intervention group than in the control group (rate ratio, 0.91 [95% CI, 0.86 to 0.97]; P = 0.002). When the data were analyzed by the number of unique patients hospitalized, only the reduction in admissions for acute myocardial infarction was statistically significant (rate ratio, 0.89 [CI, 0.79 to 0.99]; P = 0.03). End-stage kidney disease outcomes were not reported. Summaries of the limitations, consistency, and applicability of the evidence for all key questions can be found in Appendix Table 1.

Diagnostic Accuracy of OBPM

We identified 4 good-quality (24–27) and 3 fair-quality (28–30) studies examining the diagnostic accuracy of OBPM methods or protocols in untreated screening populations. Four of these studies (25–28) examined how well automated oscillometric OBPM (1 to 3 measurements) predicted results from manual sphygmomanometry (the reference standard). Among these, 3 studies (26–28) reported sensitivities of oscillometric OBPM ranging from 51% to 68% for elevated BP (systolic BP ≥140 mm Hg or diastolic BP ≥90 mm Hg), as measured by the reference method. The fourth study (25) reported a sensitivity of 91% but differed from the others in that it used a higher threshold in its definition of elevated BP (systolic BP ≥160 mm Hg or diastolic BP ≥95 mm Hg) and used a research design that minimized human error in manual BP measurement. The fair-quality study (28) reported the lowest sensitivity and used 3 different oscillometric devices, with no attempt to ensure comparability or validity among them. Overall, these 4 studies reported more consistent specificities (97% to 98%) and PPVs (76% to 84%). In 3 studies (31–33) that compared manual and automated OBPM with ABPM as the reference standard, neither manual nor automated systolic OBPM results were clearly favored.
Three diagnostic accuracy studies examined the effect of different aspects of recommended protocols for OBPM (24, 29, 30) in untreated screening populations. For investigating the value of repeated measurements, a single manual BP measurement had a high sensitivity (95%) but a moderate PPV (76%) for the average of the second and third measurements in 1 study with a protocol that included a 5-minute premeasurement rest (24). One small study found elevated BP within the normal range among normotensive participants whose legs were crossed during measurement (29), and another found falsely elevated BP above the hypertensive threshold 40 minutes after caffeine ingestion among 17% of normotensive participants (30).

Prediction of Cardiovascular Events by BP Measurement Method

We identified a reference standard for BP measurement by comparing the accuracy of ambulatory and home-based confirmatory measurement methods with office-based methods for predicting overall mortality and cardiovascular outcomes.
We evaluated the predictive value of ABPM methods for long-term cardiovascular events, after adjustment for OBPM, in 6 good-quality (34–39) and 5 fair-quality (40–44) studies. The ABPM devices used in the included trials are generally still available in the United States and have been validated against at least 1 recognized protocol (www.dableducational.org). Where reported, all ABPM devices were oscillometric and typically took measurements every 15 to 30 minutes during the day and every 30 to 60 minutes at night (Appendix Table 2). Outcomes for 24-hour, daytime, and nighttime monitoring cycles were reported in 8, 10, and 9 studies, respectively. One study that monitored BP for 48 hours was grouped with those monitoring for 24 hours (36). Results did not seem to vary by geographic region or population baseline characteristics. Each 10–mm Hg increment in 24-hour systolic ABPM, adjusted for OBPM, was consistently and statistically significantly associated with an increased risk for fatal and nonfatal stroke in 4 studies (38, 39, 41, 44). Hazard ratios ranged from 1.28 to 1.40 (Figure 1). In 6 studies, each 10–mm Hg increment in 24-hour systolic ABPM, adjusted for OBPM, was associated with an increased risk for fatal and nonfatal cardiovascular events. These results were statistically significant in 5 studies (Figure 1) (34, 36, 38, 41, 43). Hazard ratios ranged from 1.11 to 1.42. One additional study (42) reported only that ABPM predicted cardiovascular mortality in a model that included OBPM (P  < 0.001). Estimates of hazard ratios for each 5–mm Hg increment in diastolic 24-hour ABPM, adjusted for OBPM, were also generally statistically significant but were more attenuated (data not shown) (14).
Appendix Table 2. ABPM Device Characteristics
Appendix Table 2. ABPM Device Characteristics
Figure 1. Risk for cardiovascular and mortality outcomes: systolic 24-h ABPM, adjusted for OBPM. Results of included studies for key question 3a. ABPM = ambulatory blood pressure monitoring; CV = cardiovascular; HF = heart failure; HR = hazard ratio; MI = myocardial infarction; OBPM = office blood pressure measurement.
Figure 1. Risk for cardiovascular and mortality outcomes: systolic 24-h ABPM, adjusted for OBPM.
Results of included studies for key question 3a. ABPM = ambulatory blood pressure monitoring; CV = cardiovascular; HF = heart failure; HR = hazard ratio; MI = myocardial infarction; OBPM = office blood pressure measurement.
We conducted an unplanned, exploratory meta-analysis to look for relative differences among ABPM protocols. This analysis showed no apparent differences in hazard ratios for each 10–mm Hg increase in systolic BP (24-hour ABPM hazard ratio, 1.24 [CI, 1.17 to 1.30; I 2 = 8.7%]; daytime ABPM hazard ratio, 1.20 [CI, 1.12 to 1.28; I 2 = 33.3%]; nighttime ABPM hazard ratio, 1.24 [CI, 1.17 to 1.31; I 2 = 25.6%] [all controlled for OBPM]). A sensitivity analysis that used 2 additional meta-analytic methods also did not show any differences among protocols.
We also evaluated the predictive value of HBPM for long-term cardiovascular events in 5 good-quality studies (35, 45–48), 4 of which adjusted for OBPM. All showed statistically significant associations with an increased risk for cardiovascular and mortality outcomes, with hazard ratios ranging from 1.17 to 1.39 (Appendix Figure 3).
Appendix Figure 3. Risk for cardiovascular and mortality outcomes: systolic HBPM, adjusted for OBPM. Results of included studies for key question 3a. CV = cardiovascular; HBPM = home blood pressure monitoring; HR = hazard ratio; MI = myocardial infarction; OBPM = office blood pressure measurement; TIA = transient ischemic attack.
Appendix Figure 3. Risk for cardiovascular and mortality outcomes: systolic HBPM, adjusted for OBPM.
Results of included studies for key question 3a. CV = cardiovascular; HBPM = home blood pressure monitoring; HR = hazard ratio; MI = myocardial infarction; OBPM = office blood pressure measurement; TIA = transient ischemic attack.

Diagnostic Accuracy of Methods to Confirm Elevated Office BP

We considered confirmatory BP measurement methods separately from screening OBPM to identify persons who have an elevated BP at screening but are normotensive after confirmatory testing in a nonmedical setting (isolated clinic hypertension). Without confirmatory follow-up, this group may be harmed by misdiagnosis and unnecessary treatment.
We evaluated the diagnostic accuracy of confirmatory BP measurement methods by using ABPM as the reference standard, where available, subsequent to an elevated BP at screening in 6 good-quality (32, 49–53) and 21 fair-quality (31, 33, 40, 54–71) studies. Across 24 comparable studies allowing calculation, the proportion of persons with an elevated BP at screening who were hypertensive on confirmatory testing by ABPM or HBPM ranged from 35% to 95% (Figure 2). Four studies also confirmed hypertension in 58% to 96% of persons who repeated BP measurement at subsequent office visits with the same methods used at the initial screening (data not shown). Study population characteristics related to increased hypertension prevalence, such as older average age, a higher number of abnormal screening results before confirmatory testing, and a higher BP at screening, seemed to be qualitatively associated with a higher PPV for ABPM-confirmed hypertension. On the basis of screening measurement alone, the likelihood of misdiagnosis of hypertension is greater as measurements approach the threshold for a diagnosis of hypertension.
Figure 2. Proportion of elevated OBPM results confirmed by ABPM or HBPM. Results of included studies for key question 3b. ABPM = ambulatory blood pressure monitoring; HBPM = home blood pressure monitoring; OBPM = office blood pressure measurement; PPV = positive predictive value.
Figure 2. Proportion of elevated OBPM results confirmed by ABPM or HBPM.
Results of included studies for key question 3b. ABPM = ambulatory blood pressure monitoring; HBPM = home blood pressure monitoring; OBPM = office blood pressure measurement; PPV = positive predictive value.
We investigated whether using different screening and confirmatory measurement methods improves diagnostic accuracy. We found 2 studies that enrolled persons with an elevated office BP and followed up with both ABPM and repeated OBPM by the same screening method at a separate visit, but the results did not consistently show improved results with confirmatory testing (data not shown) (54, 61).

Harms of Screening for High BP

We examined several potential harms in addition to misdiagnosis and unnecessary treatment. One good-quality (72) and 3 fair-quality (73–75) trials found no statistically significant differences in psychological distress or quality of life among participants who were labeled as hypertensive or prehypertensive. One fair-quality cohort study conducted among persons who were previously unaware of their hypertension status found increases in overall absenteeism from work, absenteeism due to illness, and number and duration of illness episodes after labeling that were statistically significant at 1 year (76) and 4 years (77) of follow-up. Four fair-quality cohort studies reported sleep disturbances, discomfort, and restrictions in daily activities during the use of an ABPM device (78–81).

Rescreening Interval and Hypertension Incidence in Screened Normotensive Persons

We identified 15 good-quality (82–96) and 25 fair-quality (53, 97–120) studies that reported hypertension incidence after rescreening, and 39 of these reported incidence by a priori subgroups of interest. Studies enrolled between 275 and 115 736 participants at baseline and evaluated screening intervals of up to 6 years. The largest number (16 studies) reported results for a 5-year interval, and only 2 studies provided data for more than 1 rescreening interval (88, 99). Most studies used a diagnostic threshold of at least 140/90 mm Hg and considered the use of antihypertensive medications equivalent to a BP exceeding the diagnostic threshold. Included studies were conducted in Asia (19 studies), the United States (8 studies), Europe (10 studies), the United Kingdom, and Australia. Twenty-one studies were community-based, 12 were employment-based, and 6 were conducted in clinics.
Incidence estimates varied widely at each rescreening interval (2.2% to 4.4% at 1 year and 2.1% to 28.4% at 5 years) (Figure 3). Studies that diagnosed hypertension on the basis of multiple office visits generally showed lower incidence than those that measured BP at 1 visit. In 2 studies that reported hypertension incidence both with and without repeated OBPM at confirmatory visits, about 55% of first-visit incident hypertension cases were not confirmed (53, 97), which suggests that true incident hypertension at various intervals is likely to be at the lower end of these estimates.
Figure 3. Scatterplot of hypertension incidence, by rescreening interval. Results of included studies for key question 4a. The size of the symbol represents the number of participants in the study. HTN = hypertension.
Figure 3. Scatterplot of hypertension incidence, by rescreening interval.
Results of included studies for key question 4a. The size of the symbol represents the number of participants in the study. HTN = hypertension.
The substantial variation in hypertension incidence across studies is related in part to the criteria used to diagnose, and in some studies confirm, incident hypertension. Some variation probably also arises from differences in study populations, which highlights the importance of identifying subpopulations with a higher risk for incident hypertension that may benefit from targeted or more intensive rescreening.

Rescreening Interval in Subpopulations

Appendix Table 3 shows weighted mean hypertension incidence across studies at rescreening intervals of 1 to 5 years, stratified by a priori subpopulations. We focused our detailed evaluation on studies providing direct within-study comparisons.
Appendix Table 3. Weighted Mean Hypertension Incidence at Various Rescreening Intervals in Subgroups Identified a Priori
Appendix Table 3. Weighted Mean Hypertension Incidence at Various Rescreening Intervals in Subgroups Identified a Priori
Four studies reported incidence by age strata (Appendix Table 4) (53, 87, 89, 109). Hypertension incidence was as much as 2- to 4-fold higher in older persons (aged 40 or 45 to 60 or 65 years) than in younger persons (aged 18 to 40 or 45 years). Similarly, hypertension incidence increased with increasing baseline BP (Appendix Table 5) (85, 90, 91, 95, 107). Incidence consistently tripled between optimal (<120/80 mm Hg) and normal (120 to 129/80 to 84 mm Hg) BP categories and approximately doubled between normal and high-normal (130 to 139/85 to 89 mm Hg) categories. For example, persons with optimal BP had a low probability (2% to 9%) of developing hypertension over a 5-year period.
Appendix Table 4. Hypertension Incidence, by Age
Appendix Table 4. Hypertension Incidence, by Age
Appendix Table 5. Hypertension Incidence in Studies Reporting 3 BP Categories
Appendix Table 5. Hypertension Incidence in Studies Reporting 3 BP Categories
Hypertension incidence was generally higher among men than women, especially in younger populations (Appendix Table 6). Although incidence was also 2-fold higher in overweight persons and 3-fold higher in obese persons compared with normal-weight persons (Table 1) (53, 111), it was not increased in smokers versus nonsmokers or former smokers (data not shown) (14).
Appendix Table 6. Hypertension Incidence at Various Rescreening Intervals, by Sex
Appendix Table 6. Hypertension Incidence at Various Rescreening Intervals, by Sex
Table 1. Hypertension Incidence at Various Rescreening Intervals, by BMI
Table 1. Hypertension Incidence at Various Rescreening Intervals, by BMI
Five studies conducted in the United States reported hypertension incidence at rescreening intervals by race/ethnicity (Table 2) (84, 86, 88, 97, 105). In each study, the incidence for African Americans was nearly 2 or more times higher than for white persons at all intervals. Only 1 study directly compared additional racial or ethnic categories; it reported higher incidence rates for African Americans at 5 years (27.5%) than for Asian, white, or Hispanic persons (16.2% to 21.2%) (86).
Table 2. Hypertension Incidence at Various Rescreening Intervals, by Race/Ethnicity
Table 2. Hypertension Incidence at Various Rescreening Intervals, by Race/Ethnicity

Discussion

An earlier review of indirect evidence and the resulting USPSTF recommendation found that treatment of high BP substantially decreases the incidence of cardiovascular events (10, 12). We examined direct evidence of benefits and harms of screening programs to identify adults with high BP and found a single RCT that targeted adults aged 65 years or older. Among those randomly assigned to screening, there was a small but statistically significant reduction in hospitalizations for acute myocardial infarction. Although the results do not apply to all age groups and were potentially confounded by additional management interventions, they provide supportive evidence for the effects of a BP screening program on target cardiovascular disease events.
We then focused most of our review efforts on BP screening methods and rescreening intervals to determine accurate and timely methods for identifying persons with elevated BP who are likely to benefit from treatment. We first examined BP measurement methods used for initial, office-based screening. Surprisingly, few studies provided sufficient data to compare the diagnostic accuracy of manual sphygmomanometry with that of automated methods in screening populations. Similarly, few studies of OBPM protocols were eligible, and those that were provided limited support for repeating BP measurement at a single visit, avoiding caffeine ingestion before measurement, and keeping legs uncrossed during measurement. Studies that seemed to provide support for other recommendations, such as proper arm positioning (121–123), cuff size (124–126), and cuff deflation speed (127) (but not removal of clothing before cuff placement [122, 128, 129]), primarily reported results in terms of mean values rather than diagnostic categories or enrolled hypertensive populations. Although automated OBPM methods offer the advantages of repeated measurements in the absence of medical personnel, future evidence reviews will need to consider the applicability of the larger number of studies conducted in treated, hypertensive persons to these questions.
Blood pressure measured by mercury sphygmomanometry in the office setting is known to be associated with cardiovascular outcomes (130). We compared ABPM and HBPM with manual office methods and found that systolic ABPM consistently and statistically significantly predicted stroke and other cardiovascular outcomes independently of OBPM. In an exploratory, comparative meta-analysis (n = 13 906), we found no apparent difference among 24-hour, daytime, and nighttime ABPM protocols within our included evidence base. Our results were similar to those of a systematic review by the National Institute for Health and Clinical Excellence (131), which concluded that ABPM was superior for predicting clinical outcomes, with no protocol favored in a qualitative review of the data (n > 17 621). However, we did not evaluate certain outcomes (such as angina or revascularization) or populations with comorbid conditions (such as diabetes or kidney disease) and included only studies conducted in countries rated “very high” on the Human Development Index. Two other large meta-analyses (one that included 13 843 hypertensive patients [132] and one that analyzed 23 856 hypertensive patients and 9641 randomly recruited persons [133]) reported that nighttime systolic ABPM was a stronger predictor of cardiovascular events than daytime ABPM or OPBM. Evidence gaps suggested by these conflicting meta-analyses include the influence of treatment and age (133) and of composite outcomes and population composition on the predictive values of 24-hour, daytime, and nighttime ABPM. We also found that systolic HBPM predicted cardiovascular outcomes in a pattern similar to that of ABPM; however, too few studies were available to allow us to draw firm conclusions about HBPM.
On the basis of the prognostic evidence, we selected ABPM as the reference standard for BP measurement and for evaluating the diagnostic accuracy of other measurement methods. We regarded daytime, nighttime, or 24-hour ABPM protocols as acceptable. Improved prediction with ABPM also suggested the need for confirmation of OBPM. We found that OBPM variably predicted “true” hypertension, as defined by ABPM. Despite this variability, hypertension at screening with OBPM was not confirmed by non-OBPM methods in a large proportion of persons. Measurement error and regression to the mean may contribute to false-positive screening results with OBPM. However, some persons without confirmation of elevated BP at screening have isolated clinic hypertension. Studies have reported that the long-term outcomes of these persons are more similar to those of normotensive persons than to those of patients with sustained hypertension (134). An unplanned analysis of patients with isolated clinic hypertension in our included studies of cardiovascular prognosis also suggested that cardiovascular disease outcomes are more similar to those of persons who are normotensive at baseline than to those of persons with sustained hypertension (data not shown) (14). Given the high variability of OBPM for predicting hypertension at confirmatory testing and the importance of identifying persons who truly require treatment, confirmatory measurement is needed to avoid misdiagnosis. Ambulatory BP monitoring provides multiple measurements over time in a nonmedical setting, which potentially avoids measurement error, regression to the mean, and misdiagnosis of isolated clinic hypertension and is best correlated with long-term outcomes.
Our evidence review shows that overdiagnosis of hypertension from unconfirmed office-based screening could result in unnecessary treatment in a substantial number of persons. Although our scope did not include reviewing evidence to determine rates of harms due to unnecessary treatment and did not directly address the proportion of persons who would have isolated clinic hypertension, these considerations will be important for future reviews. We found no evidence of other serious harms of BP screening.
Finally, we investigated the best interval for rescreening of BP after a normal screening result. Guidelines make recommendations for rescreening intervals, but none are evidence-based. We found that estimates of incident hypertension at annual intervals up to 6 years were highly variable. Qualitative analysis identified a trend toward lower estimates and less variability in studies that required confirmation (for example, by repeated measurements or visits) of elevated BP at rescreening. These findings further support the importance of confirmatory BP measurement, whether initially or at rescreening. We conclude that the wide variation in incident hypertension was at least partly driven by the different population characteristics reported in the studies. The incidence of hypertension was higher in older persons, African Americans, those with an above-normal BMI, and those with a high-normal BP.
In summary, the available evidence suggests that repeated measurements may improve the diagnostic accuracy of OBPM for screening. Initially elevated BP measured by office-based methods is best confirmed by ABPM to avoid potential overdiagnosis of isolated clinic hypertension and the potential harms of unnecessary treatment. Studies of rescreening intervals of up to 6 years found a variably high incidence of hypertension overall. Hypertension incidence at rescreening was also higher at shorter intervals for persons with BP in the high-normal range, for older persons, for those with an above-normal BMI, and for African Americans compared with those without these risk factors. These results suggest that time and resources might be better directed toward improved measurement accuracy and timely measurement in higher-risk persons rather than measurement of all persons at every office visit.

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Nancy Tondreau Neely, M.D. 24 February 2015
Accurate BP measurements
How about "taking back" some mercury from the squiggly light bulbs and accurately measuring blood pressures?

Information & Authors

Information

Published In

cover image Annals of Internal Medicine
Annals of Internal Medicine
Volume 162Number 33 February 2015
Pages: 192 - 204

History

Published online: 3 February 2015
Published in issue: 3 February 2015

Keywords

Authors

Affiliations

Margaret A. Piper, PhD, MPH
From Kaiser Permanente Center for Health Research, Portland, Oregon, and HealthPartners Institute for Education and Research, Minneapolis, Minnesota.
Corinne V. Evans, MPP
From Kaiser Permanente Center for Health Research, Portland, Oregon, and HealthPartners Institute for Education and Research, Minneapolis, Minnesota.
Brittany U. Burda, MPH
From Kaiser Permanente Center for Health Research, Portland, Oregon, and HealthPartners Institute for Education and Research, Minneapolis, Minnesota.
Karen L. Margolis, MD, MPH
From Kaiser Permanente Center for Health Research, Portland, Oregon, and HealthPartners Institute for Education and Research, Minneapolis, Minnesota.
Elizabeth O'Connor, PhD
From Kaiser Permanente Center for Health Research, Portland, Oregon, and HealthPartners Institute for Education and Research, Minneapolis, Minnesota.
Evelyn P. Whitlock, MD, MPH
From Kaiser Permanente Center for Health Research, Portland, Oregon, and HealthPartners Institute for Education and Research, Minneapolis, Minnesota.
Note: This review was conducted by the Kaiser Permanente Research Affiliates Evidence-based Practice Center under contract to the AHRQ. AHRQ staff provided oversight for the project and assisted in the external review of the companion draft evidence synthesis. The views expressed in this manuscript do not represent and should not be construed to represent a determination or policy of the AHRQ or the U.S. Department of Health and Human Services.
Acknowledgment: The authors thank the following for their contributions to this project: AHRQ staff; the USPSTF; David B. Callahan, MD, Beverly B. Green, MD, MPH, Joel Handler, MD, James A. Hodgkinson, MD, MSc, Carla I. Mercado, PhD, MS, Martin G. Myers, MD, and George S. Stergiou, MD, for providing expert review of the report; Ning Smith, PhD, for providing statistical expertise; Elizabeth Webber, MS; Leslie A. Perdue, MPH; Keshia Bigler, BS; and Kevin Lutz, MFA, and Smyth Lai, MLS, at the Kaiser Permanente Center for Health Research.
Financial Support: By contract HHSA-290-2012-00151-I, Task Order no. 2 from the AHRQ.
Disclosures: Dr. Piper reports grants from the Agency for Healthcare Research and Quality during the conduct of the study. Ms. Evans reports grants from the Agency for Healthcare Research and Quality during the conduct of the study. Ms. Burda reports grants from the Agency for Healthcare Research and Quality during the conduct of the study. Dr. Margolis reports grants from the Agency for Healthcare Research and Quality during the conduct of the study and grants from the National Heart, Lung, and Blood Institute outside the submitted work. Dr. O'Connor reports grants from the Agency for Healthcare Research and Quality during the conduct of the study. Dr. Whitlock reports grants from the Agency for Healthcare Research and Quality during the conduct of the study. Authors not named here have disclosed no conflicts of interest. Disclosures can also be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M14-1539.
Corresponding Author: Reprints are available from the AHRQ Web site (www.ahrq.gov).
Current Author Addresses: Drs. Piper, O'Connor, and Whitlock; Ms. Evans; and Ms. Burda: Kaiser Permanente Center for Health Research, 3800 North Interstate Avenue, Portland, OR 97227.
Dr. Margolis: HealthPartners Institute for Education and Research, Mail Stop 21111R, PO Box 1524, Minneapolis, MN 55440.
Author Contributions: Conception and design: M.A. Piper, C.V. Evans, B.U. Burda, K.L. Margolis, E.P. Whitlock.
Analysis and interpretation of the data: M.A. Piper, C.V. Evans, B.U. Burda, K.L. Margolis, E. O'Connor, E.P. Whitlock.
Drafting of the article: M.A. Piper, C.V. Evans, B.U. Burda.
Critical revision of the article for important intellectual content: M.A. Piper, C.V. Evans, B.U. Burda, K.L. Margolis, E.P. Whitlock.
Final approval of the article: M.A. Piper, C.V. Evans, B.U. Burda, K.L. Margolis, E. O'Connor, E.P. Whitlock.
Statistical expertise: E. O'Connor.
Obtaining of funding: E.P. Whitlock.
Administrative, technical, or logistic support: B.U. Burda.
Collection and assembly of data: M.A. Piper, C.V. Evans, B.U. Burda, K.L. Margolis.
This article was published online first at www.annals.org on 23 December 2014.

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Margaret A. Piper, Corinne V. Evans, Brittany U. Burda, et al. Diagnostic and Predictive Accuracy of Blood Pressure Screening Methods With Consideration of Rescreening Intervals: A Systematic Review for the U.S. Preventive Services Task Force. Ann Intern Med.2015;162:192-204. [Epub 3 February 2015]. doi:10.7326/M14-1539

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